A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metricsMultimodal medical image fusionMultimodal databasesFusion techniquesImage fusion quality metricsBackground and objectives Over the past two decades, medical imaging...
A new contrast based multimodal medical image fusion framework Neurocomputing, 157 (2015), pp. 143-152 View PDFView articleView in ScopusGoogle Scholar [29] Z. Guo, X. Li, H. Huang, N. Guo, Q. Li Deep learning-based image segmentation on multimodal medical imaging IEEE Trans Radiat Plas...
Full size image Performance evaluation of ML on multimodal data Balanced dataset To improve the performance of the classification models trained on balanced datasets, a multimodal data fusion strategy is tentatively employed to construct ML models. Four new fused features based on physicochemical descripto...
Multimodal medical image fusion plays an important role for clinical analysis and treatment planning. Many popular medical image fusion methods based on attention mechanism have been proposed in recent years. However, there are still several drawbacks for the above methods, including blurry contour infor...
An efficient medical image fusion method using contourlet transform based on PCM An efficient medical image fusion method has been proposed based on contourlet transform and multi fusion rules. The multimodal medical images were first d... NA Al-Azzawi,HAM Sakim,AKW Abdullah - IEEE 被引量: 18...
Among deep learning techniques, deep convolutional networks are actively used for the purpose of medical image analysis. This includes application areas such as segmentation, abnormality detection, disease classification, computer aided diagnosis and retrieval. In this study, a comprehensive review of the...
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan [24th Jul., 2023] [Journal of Imaging, 2023] [Paper]A Comprehensive Survey on Generative Diffusion Models for Structured Data Heejoon Koo, To Eun Kim [7th...
Few works specifically review MMIM methods and applications that simultaneously contain medical, remote sensing, and computer vision research. Existing surveys mainly focus on a general image matching or registration task, and only briefly introduce the multimodal case as a subsection [1], [2], [28...
A multimodal medical image fusion method based on interval gradients and convolutional neural networks is proposed to overcome this problem. First, this ... X Gu,Y Xia,J Zhang - 《Bmc Medical Imaging》 被引量: 0发表: 2024年 Convolutional Neural Networks (CNN) with Quantum-Behaved Particle Swa...
Multi-Focus Image Fusion (MFIF) was designed to solve the issue of the limited depth of field inherent in the optical lens of imaging systems. In addition, MFIF extracts all the relevant information from the source image. In this study, we present a systematic review of the current literatu...